Modeling binaural loudness

A survey of data on the perception of binaurally presented sounds indicates that loudness summation across ears is less than perfect; a diotic sound is less than twice as loud as the same sound presented monaurally. The loudness model proposed by Moore et al. [J. Audio Eng. Soc. 45, 224-240 (1997)] determines the loudness of binaural stimuli by a simple summation of loudness across ears. It is described here how the model can be modified so as to give more accurate predictions of the loudness of binaurally presented sounds, including cases where the sounds at the two ears differ in level, frequency or both. The modification is based on the idea that there are inhibitory interactions between the internal representations of the signals at the two ears, such that a signal at the left ear inhibits (reduces) the loudness evoked by a signal at the right ear, and vice versa. The inhibition is assumed to spread across frequency channels. The modified model gives reasonably accurate predictions of a variety of data on the loudness of binaural stimuli, including data obtained using loudness scaling and loudness matching procedures.     

Why can a decrease in dB(A) produce an increase in loudness?

Loudness measured by the method of absolute magnitude estimation is compared to loudness calculated in accordance with ISO 532 B (International Organization for Standardization, Geneva, 1966). The measured and calculated loudness functions exhibit a similar pattern of loudness growth. Both measured and calculated loudness of a complex sound composed of a 1000-Hz tone and broadband noise is a nonmonotonic function of the overall SPL of the complex. The nonmonotonic loudness-growth pattern holds over a 30-dB range from 73.5 to 103.5. To facilitate understanding of the results, a single cycle of data is analyzed in detail. The analysis shows that loudness patterns produced in the auditory system by the tone-noise complex can account for the observed effects. Moreover, they show that the A-weighting and the loudness of the complex are negatively related. This inverse relation means that the A-weighted SPL is an inappropriate and misleading indicator of the loudness of sound combinations with heterogeneous spectral envelopes. Consequently, its suitability for noise control is diminished. A loudness meter that combines the spectral shapes of different sounds to produce an overall perceived magnitude offers greater promise.     

Moore响度计算模型的改进

与早期响度的图表计算方法相比,Moore计算模型是基于解析式的并且实现了响度值随频率、强度改变的连续计算,因此使用起来非常方便;然而,Moore模型计算公式中基本参数值的确定所依据的闻阈标准数据已被修订,并且最新研究表明,Moore模型在确定α值时所做的假设是不合理的;因此本文中(1)提出了利用耳蜗输入输出函数以确定响度函数的方法;(2)根据多个频率处的响度函数重新估计了Moore模型的参数α;(3)根据最新的闻阈标准数据和新的机理重新修订了其它基本参数;(4)利用新的模型重新计算了等响曲线并与原有模型的结果以及最新国际标准进行了对比。结论表明对1～8kHz之间的计算结果有了较大的修订,特别是能很好地预测1～2kHz之间的凸起。     

Assessment of a simplified experimental procedure to evaluate impact sound reduction of floor coverings

The impact noise reduction provided by floor coverings is usually obtained in laboratory, using the methodology described in the standard EN ISO 140-8, which requires the use of standard acoustic chambers. The construction of such chambers, following the requirements described in the EN ISO 140-1, implies a significant investment, and therefore only a limited number exists in each country. Alternatives to these standard methodologies, that allow a sufficiently accurate evaluation and require lower resources, have been interesting many researchers and manufacturers. In this paper, one such strategy is discussed, where a reduced sized slab is used to determine the noise reduction provided by floor coverings, following the procedure described in the ISO/CD 16251-1 technical document. Several resilient coverings, floating floors and floating slabs are tested and the results are compared with those obtained using the procedures described in the standards EN ISO 140-8 and EN ISO 717-2.     

Auditory analysis of the periodicity of sound and its envelope: A mathematical model

A mathematical model of the auditory analysis of periodicity of sound and its envelope is proposed. The model consists of a sequence of mathematical transformations that describe the signal processing stages. The following parameters and properties of the auditory system are taken into account: the crude analysis of the input acoustic signal accurate to the width of the aural critical band; the frequency dependence of the width of the aural critical band; the spectrum of the input signal analysis by a set of 3500 filters closely spaced in frequency; the absolute audibility thresholds at a given frequency; the time-domain analysis of both the output signals of each filter and the envelope profile with the help of the periodicity function; the pulsed activity of auditory neurons; the ability of the auditory system to memorize the spectral-time images of the signal and its individual parameters; the ability of the auditory system to form the perception of the loudness of sound, to memorize and compare the loudness of sound at different time moments, and to conclude which of them is higher or lower or whether they are equal accurate to a certain threshold; the dependence of the critical modulation bandwidth on the modulation frequency; and the dependence of the audibility thresholds of amplitude modulation on the modulation frequency. By an example of processing amplitude-modulated signals with various carrier-to-envelope frequency ratios, the model is shown to give a satisfactory explanation of their pitch and auditory estimate of the envelope period.     

A-weighted sound pressure level as a loudness/annoyance indicator for environmental sounds - Could it be improved?

A system is introduced with the purpose of showing how an auditory perception system may be built up to include the basic quantities on loudness domain. The quantities are the critical bands, the power law, and the weighting. The power law seems to be the most crucial basis for hypothesizing a loudness function. It has been shown that the power law could be applied as such by assuming the auditory perception system to have two essentially different stimuli: the intensity (sound pressure level) and pure pressure. These physically different quantities seem to be combined in the root of the power law, and in this study the roots are determined from equal-loudness contours. A loudness function is derived on the basis of this finding. By adding the weighting, a method has been constructed for assessing loudness. After defining the weighting, the equal-loudness contours are constructed and are seen to be virtually identical to the contours in ISO 226. It has also been found that the equations for deriving the contours in this standard and in the new ISO 226 may be incorrect, because there is no definition of a sensible loudness function. Finally, it is deduced that the derived weighting must be unequivocal for an auditory perception system (depending solely on the otologically representative group). Finally, the A-weighting (as part of an A-weighted sound pressure level) as such is reasonably similar to the weighting derived in this study. Therefore, this weighting is not the main problem when assessing sounds in respect to loudness. The A-weighting is thus chosen as the weighting for the indicator derived in the study for assessing environmental sounds.     

Effects of consonant-vowel intensity ratio on loudness of monosyllabic words

Previous research has suggested that speech loudness is determined primarily by the vowel in consonant-vowel-consonant (CVC) monosyllabic words, and that consonant intensity has a negligible effect. The current study further examines the unique aspects of speech loudness by manipulating consonant-vowel intensity ratios (CVRs), while holding the vowel constant at a comfortable listening level (70 dB), to determine the extent to which vowels and consonants contribute differentially to the loudness of monosyllabic words with voiced and voiceless consonants. The loudness of words edited to have CVRs ranging from -6 to +6?dB was compared to that of standard words with unaltered CVR by 10 normal-hearing listeners in an adaptive procedure. Loudness and overall level as a function of CVR were compared for four CVC word types: both voiceless consonants modified; only initial voiceless consonants modified; both voiced consonants modified; and only initial voiced consonants modified. Results indicate that the loudness of CVC monosyllabic words is not based strictly on the level of the vowel; rather, the overall level of the word and the level of the vowel contribute approximately equally. In addition to furthering the basic understanding of speech perception, the current results may be of value for the coding of loudness by hearing aids and cochlear implants.     

Loudness relations for individuals and groups in normal and impaired hearing

Individual and group loudness relations were obtained at a frequency in the region of impaired hearing for 100 people, 98 with bilateral cochlear impairment. Slope distributions were determined from absolute magnitude estimation (AME) and absolute magnitude production (AMP) of loudness; they were also derived from cross-modality matching (CMM) and AME of apparent length. With respect to both the means and the individual slope values, the two distributions closely agree. More than half of the measured deviations are less than 20%, with an overall average of -1.5%, meaning that transitivity is preserved for bilaterally impaired individuals. Moreover, over the stimulus range where cochlear impairment steepens the loudness function, both the group means and the individual slope values are clearly larger than in normal hearing. The results also show that, for groups of people with approximately similar losses, the standard deviation is a nearly constant proportion of the mean slope value giving a coefficient of variation of about 27% in normal and impaired hearing. This indicates, in accord with loudness matching, that the size of the slopes depends directly on the degree of hearing loss. The results disclose that loudness measurements obtained by magnitude scaling are able to reveal the operating characteristic of the ear for individuals.     

峰值功率等激光术语的理解与应用问题

本文根据激光术语国家标准和ISO 国际标准对某些常用激光术语概念的理解与应用问题进行了讨论,并针对国内外科技期刊和专著经常将脉冲功率与峰值功率混为一谈的问题提出了质疑,同时也指出了在激光术语使用过程中存在的其它错误现象,分析了产生类似错误的原因并给出了规范的使用方法。最后,以脉冲激光器术语定义为例通过脉冲激光振荡过程的物理原理分析提出了关于该术语定义的一些修改考虑与建议。     

Relationships between arithmetic averages of sound pressure level calculated in octave bands and Zwicker’s loudness level

Previously it has been found through a series of psychoacoustical experiments that the arithmetic average of sound pressure level calculated in octave bands is a good estimator of loudness for various kinds of environmental noise. Remarkably, the arithmetic average of sound pressure level in octave bands from 63 Hz to 4 kHz, L_m,1/1(63-4k), strongly correlates with the loudness level specified in ISO 532B, LL(Z), as well as with loudness assessment. To investigate this relationship further, a numerical study has been carried out based on Zwicker’s loudness model. As a result, practical expressions to estimate the loudness levels of general environmental noises from the sound pressure levels in octave bands from 63 Hz or 125 Hz to 4 kHz are proposed.     

A first-principles model for estimating the prevalence of annoyance with aircraft noise exposure

Numerous relationships between noise exposure and transportation noise-induced annoyance have been inferred by curve-fitting methods. The present paper develops a different approach. It derives a systematic relationship by applying an a priori, first-principles model to the findings of forty three studies of the annoyance of aviation noise. The rate of change of annoyance with day-night average sound level (DNL) due to aircraft noise exposure was found to closely resemble the rate of change of loudness with sound level. The agreement of model predictions with the findings of recent curve-fitting exercises (cf. Miedma and Vos, 1998) is noteworthy, considering that other analyses have relied on different analytic methods and disparate data sets. Even though annoyance prevalence rates within individual communities consistently grow in proportion to duration-adjusted loudness, variability in annoyance prevalence rates across communities remains great. The present analyses demonstrate that 1) community-specific differences in annoyance prevalence rates can be plausibly attributed to the joint effect of acoustic and non-DNL related factors and (2) a simple model can account for the aggregate influences of non-DNL related factors on annoyance prevalence rates in different communities in terms of a single parameter expressed in DNL units-a "community tolerance level."     

Loudness growth in individual listeners with hearing losses: a review

This letter reanalyzes data from the literature in order to test two loudness-growth models for listeners with hearing losses of primarily cochlear origin: rapid growth and softness imperception. Five different studies using different methods to obtain individual loudness functions were used: absolute magnitude estimation, cross-modality matching with string length, categorical loudness scaling, loudness functions derived from binaural loudness summation, and loudness functions derived from spectral summation of loudness. Results from each of the methods show large individual differences. Individual loudness-growth functions encompass a wide range of shapes from rapid growth to softness imperception.     

Ionospheric vertical total electron content prediction model in low-latitude regions based on long short-term memory neural network

Ionosphere delay is one of the main sources of noise affecting global navigation satellite systems, operation of radio detection and ranging systems and very-long-baseline-interferometry. One of the most important and common methods to reduce this phase delay is to establish accurate nowcasting and forecasting ionospheric total electron content models. For forecasting models, compared to mid-to-high latitudes, at low latitudes, an active ionosphere leads to extreme differences between long-term prediction models and the actual state of the ionosphere. To solve the problem of low accuracy for long-term prediction models at low latitudes, this article provides a low-latitude, long-term ionospheric prediction model based on a multi-input-multi-output, long-short-term memory neural network. To verify the feasibility of the model, we first made predictions of the vertical total electron content data 24 and 48 hours in advance for each day of July 2020 and then compared both the predictions corresponding to a given day, for all days. Furthermore, in the model modification part, we selected historical data from June 2020 for the validation set, determined a large offset from the results that were predicted to be active, and used the ratio of the mean absolute error of the detected results to that of the predicted results as a correction coefficient to modify our multi-input-multi-output long short-term memory model. The average root mean square error of the 24-hour-advance predictions of our modified model was 4.4 TECU, which was lower and better than 5.1 TECU of the multi-input-multi-output, long short-term memory model and 5.9 TECU of the IRI-2016 model.     

The measurement of loudness in individual children and adults by absolute magnitude estimation and cross-modality matching

Twelve adults and 11 children (age range 4-7 years) performed absolute magnitude estimation of the apparent lengths of lines and the loudnesses of 1000-Hz tones as well as cross-modality matching between loudness and apparent line length. Consistent with the notion that children and adults have similar impressions of loudness, there were no major differences between the absolute magnitude estimation (AME) and cross-modality matching (CMM) data of the adults and children. A direct comparison between the exponents for loudness by AME and CMM was made when a correction factor was employed to eliminate the effects of idiosyncratic use of numbers from the AME exponents. The results support the hypothesis that, with proper instructions, both children and adults can judge stimuli on an absolute scale. Specifically, for 9 out of 12 adults and 9 out of 11 children, lines and tones assigned the same number in absolute magnitude estimation were judged to be subjectively equal in cross-modality matching.     

Incorporation of loudness measures in active noise control

An attempt has been made to use a modified version of a standard active noise control algorithm in order to take into account the unique response of the human auditory system. It has been shown in the past that decreasing the sound pressure level at a location does not guarantee a similar decrease in the perceived loudness at that location. Typically, active noise control is based on minimizing the "error signal" from a mechanical device such as a microphone, whose response is nominally flat across the frequency response range of the human ear. However, if the response of the ear can be approximated by digitally filtering the error signal before it reaches the adaptive controller, one can, in effect, minimize the more subjective loudness level, as opposed to the sound pressure level. The work reported here entails simulating active noise control based upon minimizing perceived loudness for a collection of input noise signals. A comparison of the loudness of the resulting error signal is made to the loudness of that resulting from standard sound pressure level minimization. It has been found that the effectiveness of this technique is largely dependent upon the nature of the input noise signal. Furthermore, this technique is judged to be worth considering for use with applications of active noise control where the uncontrolled noise more prominently constitutes low range audio frequencies (approximately 30 Hz-100 Hz) than medium range audio frequencies (approximately 300 Hz-600 Hz).     

Further evaluation of a model of loudness perception applied to cochlear hearing loss.

This paper describes further tests of a model for loudness perception in people with cochlear hearing loss. It is assumed that the hearing loss (the elevation in absolute threshold) at each audiometric frequency can be partitioned into a loss due to damage to outer hair cells (OHCs) and a loss due to damage to inner hair cells (IHCs) and/or neurons. The former affects primarily the active mechanism that amplifies the basilar membrane (BM) response to weak sounds. It is modeled by increasing the excitation level required for threshold, which results in a steeper growth of specific loudness with increasing excitation level. Loss of frequency selectivity, which results in broader excitation patterns, is also assumed to be directly related to the OHC loss. IHC damage is modeled by an attenuation of the calculated excitation level at each frequency. The model also allows for the possibility of complete loss of IHCs or functional neurons at certain places within the cochlea ("dead" regions). The parameters of the model (OHC loss at each audiometric frequency, plus frequency limits of the dead regions) were determined for three subjects with unilateral cochlear hearing loss, using data on loudness matches between sinusoids presented alternately to their two ears. Further experiments used bands of noise that were either 1-equivalent rectangular bandwidth (ERB) wide or 6-ERBs wide, centered at 1 kHz. Subjects made loudness matches for these bands of noise both within ears and across ears. The model was reasonably accurate in predicting the results of these matches without any further adjustment of the parameters.     

Effects of vocal loudness variation on spectrum balance as reflected by the alpha measure of long-term-average spectra of speech

The overall slope of long-term-average spectrum (LTAS) decreases if vocal loudness increases. Therefore, changes of vocal loudness also affects the alpha measure, defined as the ratio of spectrum intensity above and below 1000 Hz. The effect on alpha of loudness variation was analyzed in 15 male and 16 female voices reading a text at different degrees of vocal loudness. The mean range of equivalent sound level (L(eq)) amounted to about 28 dB and the mean range of alpha to 19.0 and 11.7 dB for the female and male subjects. The L(eq) vs. alpha relationship could be approximated with a quadratic function, or by a linear equation, if softest phonation was excluded. Using such equations alpha was computed for all values of L(eq) observed for each subject and compared with observed values. The maximum and the mean absolute errors were 2.4 dB and between 0.1 and 0.6 dB. When softest phonation was disregarded and linear equations were used, the maximum error was less than 2 dB and the mean absolute errors were between 0.2 and 0.7 dB. The strong correlation between L(eq) and alpha indicates that for a voice L(eq) can be used for predicting alpha.     

The( p,q) inflation model

In this paper we propose a new inflation model named( p, q) inflation model in which the inflaton potential contains both positive and negative powers of inflaton field in the polynomial form. We derive the accurate predictions of the canonical single-field slow-roll inflation model. Using these formula, we show that our inflation model can easily generate a large amplitude of tensor perturbation and a negative running of spectral index with large absolute value.     

A sound quality-based investigation of the HVAC system noise of an automobile model

Using methods and techniques of sound quality engineering, the noise of the heating, ventilation and air-conditioning system (HVAC) of an automobile model was studied. Such noise has a great influence on vehicle acoustical comfort and on overall quality perception of a vehicle. The study was divided into two steps. The first step aimed to identify the most significant attributes that contribute to the perception of similarity or dissimilarity of this kind of noise, using the paired comparison technique and correlation of the results with psychoacoustic models. Loudness, spectral composition and tonality, represented by the psychoacoustic models of loudness, sharpness, tone-to-noise ratio and prominence were found to be the most important dimensions for the perception of similarity and dissimilarity of HVAC-noise.In the second step of the study a model to predict subjective response to HVAC sounds using the semantic differential technique was developed. In particular the perception of annoyance was studied and it is shown that the annoyance caused by the HVAC noise can be satisfactorily described by Zwicker’s stationary loudness model, provided that the HVAC noises do not present tonal components. The loudness model also predicts scores on a quiet/loud scale. Both results confirm the power of the loudness dimension and its model introduced by Zwicker for the overall quality of stationary broadband sounds without slow fluctuations or tonal components. From the annoyance model developed in this study a maximum acceptable loudness level for HVAC-systems can be determined.     

A model for the prediction of breathiness in vowels

The perception of breathiness in vowels is cued by multiple acoustic cues, including changes in aspiration noise (AH) and the open quotient (OQ) [Klatt and Klatt, J. Acoust. Soc. Am. 87(2), 820-857 (1990)]. A loudness model can be used to determine the extent to which AH masks the harmonic components in voice. The resulting "partial loudness" (PL) and loudness of AH ["noise loudness" (NL)] have been shown to be good predictors of perceived breathiness [Shrivastav and Sapienza, J. Acoust. Soc. Am. 114(1), 2217-2224 (2003)]. The levels of AH and OQ were systematically manipulated for ten synthetic vowels. Perceptual judgments of breathiness were obtained and regression functions to predict breathiness from the ratio of NL to PL (η) were derived. Results show that breathiness can be modeled as a power function of η. The power parameter of this function appears to be affected by the fundamental frequency of the vowel. A second experiment was conducted to determine if the resulting power function could estimate breathiness in a different set of voices. The breathiness of these stimuli, both natural and synthetic, was determined in a listening test. The model estimates of breathiness were highly correlated with perceptual data but the absolute predicted values showed some discrepancies.